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All Journal The Indonesian Journal of Computer Science
Tsedura, Nyaradzo Alice
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Computer Science & IT Electrical & Electronics Engineering Engineering

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An Assessment of the Visibility of Particular Swarm Intelligence Technologies in the Resolution of the Object Classification Problem Tsedura, Nyaradzo Alice; Bhero, Ernest; Chibaya, Colin
The Indonesian Journal of Computer Science Vol. 13 No. 5 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i5.4275

Abstract

This article assesses the visibility of five swarm intelligence algorithms in resolving the object classification problem explicitly particle swarm optimization, artificial bee colonies, ant colony optimization, bacterial foraging optimization, and the Social Spider Optimization. 58 articles in total were reviewed and used as the ground on which this assessment was based on. Primarily articles were grouped into two categories namely the articles which directly resolve the object classification problem and those which in directly resolve the object classification problem followed by a further grouping to indicate articles that were directly linked to the object classification problem through swarm technology and finally grouped by the aim. Three aims were observable which are to modify, to improve and to investigate. More than 70% of the articles aimed at either modifying or improving already existing swarm intelligence algorithms. PSO was the most dominant algorithm of the five technologies assessed. Interesting to note was that although all these algorithms were applied there is no formal representation of knowledge in this domain.
Co-Authors Bhero, Ernest Chibaya, Colin